import pandas as pd
import matplotlib.pyplot as plt
import plotly.express as px

x=pd.read_csv('shopify1.csv')
x

	order_id	shop_id	user_id	order_amount	total_items	payment_method	created_at
0	1	53	746	224	2	cash	13/03/2017 12:36
1	2	92	925	90	1	cash	03/03/2017 17:38
2	3	44	861	144	1	cash	14/03/2017 04:23
3	4	18	935	156	1	credit_card	26/03/2017 12:43
4	5	18	883	156	1	credit_card	01/03/2017 04:35
...	...	...	...	...	...	...	...
4995	4996	73	993	330	2	debit	30/03/2017 13:47
4996	4997	48	789	234	2	cash	16/03/2017 20:36
4997	4998	56	867	351	3	cash	19/03/2017 05:42
4998	4999	60	825	354	2	credit_card	16/03/2017 14:51
4999	5000	44	734	288	2	debit	18/03/2017 15:48

5000 rows × 7 columns

z=x['order_amount'].mean()
z
y=x['order_amount']

px.line(x,x='payment_method',y='order_amount')

px.bar(x, x="payment_method", y="order_amount", color="payment_method")

AS you can see the major transaction are done in credit card for the sneakers. Also some people might not have credit card as they have debit card or cash sales might be less because of this. We could add options for debit based emi for increasing sales.